CN116905089B - Method for controlling furnace temperature big data driving thermal field based on indium phosphide monocrystal production process - Google Patents
Method for controlling furnace temperature big data driving thermal field based on indium phosphide monocrystal production process Download PDFInfo
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- CN116905089B CN116905089B CN202310852074.7A CN202310852074A CN116905089B CN 116905089 B CN116905089 B CN 116905089B CN 202310852074 A CN202310852074 A CN 202310852074A CN 116905089 B CN116905089 B CN 116905089B
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- GPXJNWSHGFTCBW-UHFFFAOYSA-N Indium phosphide Chemical compound [In]#P GPXJNWSHGFTCBW-UHFFFAOYSA-N 0.000 title claims abstract description 57
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 41
- 238000000034 method Methods 0.000 title claims abstract description 32
- 239000013078 crystal Substances 0.000 claims abstract description 100
- 238000001816 cooling Methods 0.000 claims abstract description 13
- 238000012797 qualification Methods 0.000 claims abstract description 9
- 230000008569 process Effects 0.000 claims abstract description 7
- 238000009529 body temperature measurement Methods 0.000 claims description 6
- 238000010224 classification analysis Methods 0.000 claims description 3
- 238000002425 crystallisation Methods 0.000 claims description 3
- 230000008025 crystallization Effects 0.000 claims description 3
- 239000012535 impurity Substances 0.000 claims description 3
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 230000001939 inductive effect Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 239000002994 raw material Substances 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 229910052810 boron oxide Inorganic materials 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- JKWMSGQKBLHBQQ-UHFFFAOYSA-N diboron trioxide Chemical compound O=BOB=O JKWMSGQKBLHBQQ-UHFFFAOYSA-N 0.000 description 1
- 239000002019 doping agent Substances 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 229910052738 indium Inorganic materials 0.000 description 1
- APFVFJFRJDLVQX-UHFFFAOYSA-N indium atom Chemical compound [In] APFVFJFRJDLVQX-UHFFFAOYSA-N 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 229910052698 phosphorus Inorganic materials 0.000 description 1
- 239000011574 phosphorus Substances 0.000 description 1
- 239000010453 quartz Substances 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 1
- 238000007711 solidification Methods 0.000 description 1
- 230000008023 solidification Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 239000000758 substrate Substances 0.000 description 1
Classifications
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- C—CHEMISTRY; METALLURGY
- C30—CRYSTAL GROWTH
- C30B—SINGLE-CRYSTAL GROWTH; UNIDIRECTIONAL SOLIDIFICATION OF EUTECTIC MATERIAL OR UNIDIRECTIONAL DEMIXING OF EUTECTOID MATERIAL; REFINING BY ZONE-MELTING OF MATERIAL; PRODUCTION OF A HOMOGENEOUS POLYCRYSTALLINE MATERIAL WITH DEFINED STRUCTURE; SINGLE CRYSTALS OR HOMOGENEOUS POLYCRYSTALLINE MATERIAL WITH DEFINED STRUCTURE; AFTER-TREATMENT OF SINGLE CRYSTALS OR A HOMOGENEOUS POLYCRYSTALLINE MATERIAL WITH DEFINED STRUCTURE; APPARATUS THEREFOR
- C30B29/00—Single crystals or homogeneous polycrystalline material with defined structure characterised by the material or by their shape
- C30B29/10—Inorganic compounds or compositions
- C30B29/40—AIIIBV compounds wherein A is B, Al, Ga, In or Tl and B is N, P, As, Sb or Bi
-
- C—CHEMISTRY; METALLURGY
- C30—CRYSTAL GROWTH
- C30B—SINGLE-CRYSTAL GROWTH; UNIDIRECTIONAL SOLIDIFICATION OF EUTECTIC MATERIAL OR UNIDIRECTIONAL DEMIXING OF EUTECTOID MATERIAL; REFINING BY ZONE-MELTING OF MATERIAL; PRODUCTION OF A HOMOGENEOUS POLYCRYSTALLINE MATERIAL WITH DEFINED STRUCTURE; SINGLE CRYSTALS OR HOMOGENEOUS POLYCRYSTALLINE MATERIAL WITH DEFINED STRUCTURE; AFTER-TREATMENT OF SINGLE CRYSTALS OR A HOMOGENEOUS POLYCRYSTALLINE MATERIAL WITH DEFINED STRUCTURE; APPARATUS THEREFOR
- C30B11/00—Single-crystal growth by normal freezing or freezing under temperature gradient, e.g. Bridgman-Stockbarger method
- C30B11/003—Heating or cooling of the melt or the crystallised material
-
- C—CHEMISTRY; METALLURGY
- C30—CRYSTAL GROWTH
- C30B—SINGLE-CRYSTAL GROWTH; UNIDIRECTIONAL SOLIDIFICATION OF EUTECTIC MATERIAL OR UNIDIRECTIONAL DEMIXING OF EUTECTOID MATERIAL; REFINING BY ZONE-MELTING OF MATERIAL; PRODUCTION OF A HOMOGENEOUS POLYCRYSTALLINE MATERIAL WITH DEFINED STRUCTURE; SINGLE CRYSTALS OR HOMOGENEOUS POLYCRYSTALLINE MATERIAL WITH DEFINED STRUCTURE; AFTER-TREATMENT OF SINGLE CRYSTALS OR A HOMOGENEOUS POLYCRYSTALLINE MATERIAL WITH DEFINED STRUCTURE; APPARATUS THEREFOR
- C30B11/00—Single-crystal growth by normal freezing or freezing under temperature gradient, e.g. Bridgman-Stockbarger method
- C30B11/006—Controlling or regulating
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- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Crystallography & Structural Chemistry (AREA)
- Materials Engineering (AREA)
- Metallurgy (AREA)
- Organic Chemistry (AREA)
- Inorganic Chemistry (AREA)
- Crystals, And After-Treatments Of Crystals (AREA)
Abstract
The invention discloses a method for driving thermal field control based on big furnace temperature data in the production process of indium phosphide single crystals, which comprises the steps of obtaining measured temperature data in the production furnace of the indium phosphide single crystals; classifying and calculating the acquired temperature data to obtain a cooling rate; classifying and analyzing the calculated data, establishing a database, combining a data driving system, and predicting the optimal temperature required by production according to the existing temperature to establish an optimal temperature prediction model; and predicting the optimal temperature required by each link of the growth of the indium phosphide single crystal through a prediction model, and giving an optimal control input strategy in advance. After each new round of single crystal growth, the round of data statistics are collected and summarized into a database, so that a dynamic database is formed. The method utilizes temperature data in the production process of the indium phosphide single crystal to analyze the rule of crystal growth at different temperatures and forecast the optimal temperature required by production, so that the growth process of the indium phosphide single crystal always maintains the optimal temperature, and the production rate and the crystal qualification rate of the indium phosphide single crystal are improved.
Description
Technical Field
The invention relates to a method for driving thermal field control based on big furnace temperature data in the production process of indium phosphide single crystals, which is applied to the production of the indium phosphide single crystals and aims to improve the production rate and the crystal qualification rate of the indium phosphide single crystals.
Background
Indium phosphide is a compound of phosphorus and indium, and indium phosphide has excellent characteristics as a semiconductor material. The semiconductor device manufactured by using the indium phosphide substrate has the characteristics of high saturated electron drift speed, proper optical fiber low-loss communication with light-emitting wavelength, strong radiation resistance, good heat conductivity, high photoelectric conversion efficiency, higher forbidden bandwidth and the like, so that the indium phosphide can be widely applied to manufacturing optical module devices, sensing devices, high-end radio frequency devices and the like, and has irreplaceable functions and important development prospects in the industries of 5G/6G mobile communication, laser and optical detection equipment, artificial intelligence, automatic driving, solar cells, high-speed rails, aerospace and the like.
The existing preparation methods at present mainly comprise a liquid-sealed Czochralski (LEC) method, a Vertical Bridgman (VB) method and a vertical gradient solidification (VGF) method, but the indium phosphide single crystal product prepared by the LEC method does not meet the market demand, so that the VB method and the VGF method are mainly adopted at present.
For the preparation of indium phosphide single crystal, it is difficult to directly synthesize the indium phosphide single crystal by adopting simple substance raw materials, but indium phosphide polycrystal is used as an intermediate body to grow the indium phosphide single crystal, in the VGF method process for preparing the indium phosphide single crystal, indium phosphide polycrystal is used as a matrix, boron oxide is used as an impregnating agent, and then the raw materials such as doping agent and red phosphorus are matched with a crucible in a quartz tube to seal, and gradient heating is carried out, so that the melted indium phosphide polycrystal is melted and the single crystal is solidified and grown at a seed crystal. However, the current VGF method has lower efficiency of preparing indium phosphide single crystal, and the grown indium phosphide single crystal has shorter length, and can form defects such as twin crystal, polycrystal and the like.
Disclosure of Invention
Based on the defects existing in the prior art, the invention aims to provide a furnace temperature big data driving thermal field control method based on the indium phosphide single crystal production process, which has high production rate and low polycrystalline twin rate of a single crystal finished product.
In order to achieve the above purpose, the invention adopts the following technical scheme: a method for driving thermal field control based on big furnace temperature data in the production process of indium phosphide single crystals comprises the following steps:
(a) Collecting temperature data of all temperature measuring points in all indium phosphide single crystal growth furnaces;
(b) Classifying the obtained temperature data, including: sorting the indium phosphide monocrystal according to the qualification standard, and analyzing the variability, wherein the qualification standard comprises the following steps: (1) Whether the total length of the indium phosphide monocrystal crystal reaches the budget standard or not; (2) whether the surface of the indium phosphide single crystal meets the standard or not; (3) Whether the interior of the indium phosphide single crystal is pure, has impurities or polycrystal or twin crystal; (4) Whether the available length and size in the indium phosphide single-crystal meet the standards or not; then, the obtained temperature data and the temperature measurement time interval are utilized to calculate the cooling rate of different monocrystal growth processes;
(c) And establishing a database after classifying and analyzing the obtained crystal cooling rates, wherein the method for analyzing the difference of different crystal cooling rates comprises the following steps: (1) Maximum values of temperature measurement between different steps of the standard crystal and the unachievable crystal at the same position are analyzed, and the maximum allowable temperature rate of the temperature field at the same position is analyzed; (2) The standard reaching crystal and the unachievable crystal are measured at the same position to obtain the extreme values of the cooling rates in different steps; (3) Different temperature variation differences among different crystals produced in different time periods of the same single crystal furnace; after the analysis is completed, a database is established according to the classification analysis result and the temperature data, and an optimal temperature system prediction model is analyzed and established by combining a data driving system; combining with a data driving system to establish an optimal temperature system prediction model;
(d) Obtaining the optimal temperature required by the crystallization process of indium phosphide single crystal production according to a prediction model, giving out an optimal control input strategy in advance, and inputting control parameters into a single crystal furnace control box;
(e) After the new round of single crystal growth is completed, the round of data is statistically collected and analyzed, and is put into the original database, so that a dynamic database is formed.
In the step d, according to the optimal temperature prediction model obtained in the step C, the optimal temperature required by each step is input into a single crystal furnace temperature control box in advance when the furnace is empty, the control box transmits signals to 4 temperature control points C1, C2, C3 and C4, and the furnace wire current is controlled according to the input control signals so as to achieve the purpose of controlling the temperature.
In the step e, when a new round of single crystal production is performed, the actual furnace temperature in the production process is required to be measured in real time, and after each production is finished, the obtained temperature data and the growth condition of the crystal are collected, and the obtained temperature information is summarized into a database; the database is continuously updated in the single crystal production to form a dynamic database, so that the control system is convenient to optimize, and the productivity is improved.
The beneficial effects of the invention are as follows: the provided furnace temperature big data driving thermal field control method based on the indium phosphide single crystal production process is based on the furnace temperature big data of the indium phosphide single crystal production process, classifies and analyzes the influence of temperature on the formation of the indium phosphide single crystal, establishes a database of the inductive analysis data content and establishes an optimal temperature prediction model by combining a data driving system, and then applies the obtained optimal temperature prediction model to the actual indium phosphide single crystal production so as to achieve the purposes of improving the indium phosphide single crystal production rate, reducing the polycrystal and twin crystal of a single crystal finished product, meanwhile, the crystal bar length of the obtained product can be obviously increased, the quality of the crystal is also improved, and the production benefit of the product is high.
Drawings
FIG. 1 is a schematic flow chart of a thermal field control method based on temperature big data driving in the invention;
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1, the temperature data-based driving thermal field control method provided by the invention comprises the following steps:
(a) Collecting all temperature data of different flows of 8 temperature measuring points T1, T2, T3, T4, T5, T6, T7 and T8 in an indium phosphide single crystal production furnace;
(b) Classifying the obtained temperature data, including: sorting the indium phosphide monocrystal according to the qualification standard, and analyzing the variability, wherein the qualification standard comprises the following steps: (1) Whether the total length of the indium phosphide monocrystal crystal reaches the budget standard or not; (2) whether the surface of the indium phosphide single crystal meets the standard or not; (3) Whether the interior of the indium phosphide single crystal is pure, has impurities or polycrystal or twin crystal; (4) The available length and size of the indium phosphide monocrystal can meet the standards. Then, the obtained temperature data and the temperature measurement time interval are utilized to calculate the cooling rate of different monocrystal growth processes;
(c) B, analyzing the influence of temperature on crystal growth according to the cooling rates under different categories obtained in the step b, and finding out the rule of crystal growth under different temperature changes; the ways in which the difference in cooling rates of different crystals is analyzed include: (1) Maximum values of temperature measurement between different steps of the standard crystal and the unachievable crystal at the same position are analyzed, and the maximum allowable temperature rate of the temperature field at the same position is analyzed; (2) The standard reaching crystal and the unachievable crystal are measured at the same position to obtain the extreme values of the cooling rates in different steps; (3) Different temperature variation differences among different crystals produced in different time periods of the same single crystal furnace; after the analysis is completed, a database is established according to the classification analysis result and the temperature data, and an optimal temperature system prediction model is analyzed and established by combining a data driving system.
(d) And c, obtaining the optimal temperature required by the crystallization process of indium phosphide single crystal production according to the optimal temperature prediction model obtained in the step c, and giving an optimal control input strategy in advance. The obtained optimal production temperature of each step is input into a single crystal furnace temperature control box when the furnace is empty, a control signal is transmitted to temperature control points C1, C2, C3 and C4 by the control box, furnace wire current is controlled according to the input control signal, and gradient temperature change is started in the furnace, so that the aim of controlling the temperature is fulfilled.
(e) Measuring the actual furnace temperature in the production process in real time when a new round of single crystal production is carried out each time, collecting the obtained temperature data and the growth condition of the crystal after each production is finished, including the temperature data in the furnace, the yield and the qualification rate of the indium phosphide single crystal, and inducing the obtained temperature information into an original database; the database is continuously updated in the single crystal production to form a dynamic database, so that the control system is convenient to optimize, and the productivity is improved.
The foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (3)
1. A method for driving thermal field control based on big furnace temperature data in the production process of indium phosphide single crystals comprises the following steps:
(a) Collecting temperature data of all temperature measuring points in all indium phosphide single crystal growth furnaces;
(b) Classifying the obtained temperature data, including: sorting the indium phosphide monocrystal according to the qualification standard, and analyzing the variability, wherein the qualification standard comprises the following steps: (1) Whether the total length of the indium phosphide monocrystal crystal reaches the budget standard or not; (2) whether the surface of the indium phosphide single crystal meets the standard or not; (3) Whether the interior of the indium phosphide single crystal is pure, has impurities or polycrystal or twin crystal; (4) Whether the available length and size in the indium phosphide single-crystal meet the standards or not; then, the obtained temperature data and the temperature measurement time interval are utilized to calculate the cooling rate of different monocrystal growth processes;
(c) And establishing a database after classifying and analyzing the obtained crystal cooling rates, wherein the method for analyzing the difference of different crystal cooling rates comprises the following steps: (1) Maximum values of temperature measurement between different steps of the standard crystal and the unachievable crystal at the same position are analyzed, and the maximum allowable temperature rate of the temperature field at the same position is analyzed; (2) The standard reaching crystal and the unachievable crystal are measured at the same position to obtain the extreme values of the cooling rates in different steps; (3) Different temperature variation differences among different crystals produced in different time periods of the same single crystal furnace; after the analysis is completed, a database is established according to the classification analysis result and the temperature data, and an optimal temperature system prediction model is analyzed and established by combining a data driving system; combining with a data driving system to establish an optimal temperature system prediction model;
(d) Obtaining the optimal temperature required by the crystallization process of indium phosphide single crystal production according to a prediction model, giving out an optimal control input strategy in advance, and inputting control parameters into a single crystal furnace control box;
(e) After the new round of single crystal growth is completed, the round of data is statistically collected and analyzed, and is put into the original database, so that a dynamic database is formed.
2. The method for driving thermal field control based on furnace temperature big data in the production process of indium phosphide single crystals according to claim 1, wherein the method comprises the following steps: in the step d, according to the optimal temperature prediction model obtained in the step C, the optimal temperature required by each step is input into a single crystal furnace temperature control box in advance when the furnace is empty, the control box transmits signals to 4 temperature control points C1, C2, C3 and C4, and the furnace wire current is controlled according to the input control signals so as to achieve the purpose of controlling the temperature.
3. The method for driving thermal field control based on furnace temperature big data in the production process of indium phosphide single crystals according to claim 1, wherein the method comprises the following steps: in the step e, when a new round of single crystal production is carried out, the actual furnace temperature in the production process is required to be measured in real time, and after each production is finished, the obtained temperature data and the growth condition of the crystal are collected, and the obtained temperature information is summarized into a database; the database is continuously updated in the single crystal production to form a dynamic database, so that the control system is convenient to optimize, and the productivity is improved.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108754599A (en) * | 2018-05-31 | 2018-11-06 | 西安理工大学 | A kind of silicon monocrystal growth temprature control method based on finite element numerical simulation |
| CN113638048A (en) * | 2021-07-15 | 2021-11-12 | 云南鑫耀半导体材料有限公司 | Method for growing indium phosphide single crystal by VGF method |
| CN115404542A (en) * | 2021-05-28 | 2022-11-29 | 隆基绿能科技股份有限公司 | Single crystal Czochralski growth method, apparatus, equipment and computer readable storage medium |
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| JP5116222B2 (en) * | 2005-08-12 | 2013-01-09 | Ｓｕｍｃｏ Ｔｅｃｈｘｉｖ株式会社 | Single crystal manufacturing apparatus and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108754599A (en) * | 2018-05-31 | 2018-11-06 | 西安理工大学 | A kind of silicon monocrystal growth temprature control method based on finite element numerical simulation |
| CN115404542A (en) * | 2021-05-28 | 2022-11-29 | 隆基绿能科技股份有限公司 | Single crystal Czochralski growth method, apparatus, equipment and computer readable storage medium |
| CN113638048A (en) * | 2021-07-15 | 2021-11-12 | 云南鑫耀半导体材料有限公司 | Method for growing indium phosphide single crystal by VGF method |
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